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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗

Field Testing of a Hierarchical Model-Free Transactive Control Strategy in a Residential House

Demand response plays an important role in addressing the uncertain, intermittent, and variable nature of renewable energy sources. However, to be effective, it requires a significant amount of demand load flexibility, in which buildings are important flexible assets for electricity systems. In this regard, many transactive control tools have been developed to harness this demand flexibility. Yet, such tools are mostly simulation-based or deal with a single load, which may not be sufficient to demonstrate their effectiveness. Towards this end, this paper presents a field implementation and testing of a hierarchical model-free transactive control strategy using residential building thermostatically controlled loads. The transactive control implementation incorporates elements of virtual battery, game theory, and model-free control mechanisms. Experimental field-testing results are provided to demonstrate the effectiveness of the proposed transactive control strategy.

Olama, Mohammed M.↗

Evaluation of Centralized Model Based FLISR in a Lab Setup

Utilities are installing advanced distribution management systems (ADMS) around the globe to improve the sensing and control of distribution systems. ADMS is becoming a critical component to improve the resiliency and reliability of distribution systems. These management systems host a multitude of applications that can be used to sense, control, and operate distribution systems. Fault location, isolation, and service restoration (FLISR) is one of the ADMS applications that is critical to improving resilience during fault conditions. FLISR applications use smart, controllable devices that are installed in the distribution system for FLISR operation. These controllable devices include distributed energy resources (DER) and reclosers. Evaluating such ADMS applications before installation in the field can help de-risk the field implementation and avoid costly failures in the field. This paper presents a background on experimental setup that are typically used to evaluate ADMS applications. This is followed by briefly presenting the setup used to evaluate the FLISR application in an off-the-shelf ADMS tool. Finally, results from the evaluation experiments are presented.

94 GMLC - Grid Modernization Laboratory Consortium↗

Reliable edge machine learning hardware for scientific applications

Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations of ML algorithms: enabling bit-accurate functional simulations for performance validation in experimental software frameworks, verifying those ML models are robust under extreme quantization and pruning, and enabling ultra-fine-grained model inspection for efficient fault tolerance. We discuss approaches to developing and validating reliable algorithms at the scientific edge under such strict latency, resource, power, and area requirements in extreme experimental environments. We study metrics for developing robust algorithms, present preliminary results and mitigation strategies, and conclude with an outlook of these and future directions of research towards the longer-term goal of developing autonomous scientific experimentation methods for accelerated scientific discovery.

Baldi, Tommaso↗

Calculation of the Geometric Factor in a New Experiment Aimed at Studying Radiative Neutron Decay

A new experiment aimed at studying radiative neutron decay is proposed. The respective experimental procedure reduces to measuring the time spectra of triple coincidences of the emitted photon, beta electron, and recoil proton along with the spectrum of double coincidences of ordinary decay products. By means of this procedure, we were able to measure for the first time the branching ratio for radiative neutron decay, BR = (3.2 ± 1.6) × 10{sup −3} (at a confidence level of C.L. = 99.7%, the photon energy being in excess of 35 keV) in 2005 at our old setup. The average value of this branching ratio was greater by a factor of 1.5 than its theoretical counterpart calculated on the basis of the Standard Model. However, we cannot state that we have seen a deviation fromthe StandardModel prediction since the experimental error was quite large in that experiment. The present study is devoted to implementing, by means of the popular Geant4 code package, a computer analog of the respective experiment at a new facility. Our calculations reveal that the resulting geometri©factor values make it possible to a accumulate, in a live experiment, a data sample sufficient for measuring the above branching ratio to a precision of a few percent.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Extraction of the electron excess temperature in terahertz quantum cascade lasers from laser characteristics

Abstract We propose a method to extract the upper laser level’s (ULL’s) excess electronic temperature from the analysis of the maximum light output power ( P max ) and current dynamic range Δ J d = ( J max − J th ) of terahertz quantum cascade lasers (THz QCLs). We validated this method, both through simulation and experiment, by applying it on THz QCLs supporting a clean three-level system. Detailed knowledge of electronic excess temperatures is of utmost importance in order to achieve high temperature performance of THz QCLs. Our method is simple and can be easily implemented, meaning an extraction of the excess electron temperature can be achieved without intensive experimental effort. This knowledge should pave the way toward improvement of the temperature performance of THz QCLs beyond the state-of-the-art.

47 OTHER INSTRUMENTATION↗

The ASC-V&V Program [Slides]

The fundamental goal of the ASC-V&V Program is to obtain a quantitative understanding of our customers’ needs and priorities, and use it to assess applicability of numerical models of physical phenomena to physics questions, sensitivity of physics questions to physical phenomena, fidelity of a numerical implementation to the theory, the bounds of validity of theories, fidelity and coverage of experimental data relative to regimes of interest for physics questions, in order to warn users of IC codes and PEM data when simulations may lead to unsupported conclusions, and provide estimates of uncertainties on figures of merit calculated by the simulations.

97 MATHEMATICS AND COMPUTING↗

High Order Wall-Modeled Large-Eddy Simulation on Mixed Unstructured Meshes

In the present study, an algebraic equilibrium wall model previously developed for hexahedral elements is extended to handle mixed meshes including prismatic, tetrahedral, and pyramidal elements in the context of a discontinuous high-order method. This extension is needed for complex geometries, for which high-order mixed elements (e.g., tetrahedral and pyramidal elements) are often necessary near solid walls to avoid meshing challenges. Various design decisions are discussed to achieve the best performance on massively parallel CPU/GPU architectures for a production-level high-order large-eddy simulation solver based on the flux reconstruction/correction procedure via reconstruction method, hpMusic. The extension to other elements is first evaluated using a benchmark channel flow problem at various Reynolds numbers. After that, flow over the NASA high-lift Common Research Model (CRM-HL) from the 4th AIAA High-lift Prediction Workshop is computed to further test the new implementation. Computational results at the third- and fourth-order accuracies are compared with experimental data.

Engineering↗

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗

Gray-level transformations for interactive image enhancement

A gray-level transformation method suitable for interactive image enhancement was presented. It is shown that the well-known histogram equalization approach is a special case of this method. A technique for improving the uniformity of a histogram is also developed. Experimental results which illustrate the capabilities of both algorithms are described. Two proposals for implementing gray-level transformations in a real-time interactive image enhancement system are also presented.

Fittes, B. A.↗

Cluster compression algorithm: A joint clustering/data compression concept

The Cluster Compression Algorithm (CCA), which was developed to reduce costs associated with transmitting, storing, distributing, and interpreting LANDSAT multispectral image data is described. The CCA is a preprocessing algorithm that uses feature extraction and data compression to more efficiently represent the information in the image data. The format of the preprocessed data enables simply a look-up table decoding and direct use of the extracted features to reduce user computation for either image reconstruction, or computer interpretation of the image data. Basically, the CCA uses spatially local clustering to extract features from the image data to describe spectral characteristics of the data set. In addition, the features may be used to form a sequence of scalar numbers that define each picture element in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. Various forms of the CCA are defined and experimental results are presented to show trade-offs and characteristics of the various implementations. Examples are provided that demonstrate the application of the cluster compression concept to multi-spectral images from LANDSAT and other sources.

Hilbert, E. E.↗

Analysis of data systems requirements for global crop production forecasting in the 1985 time frame

Data systems concepts that would be needed to implement the objective of the global crop production forecasting in an orderly transition from experimental to operational status in the 1985 time frame were examined. Information needs of users were converted into data system requirements, and the influence of these requirements on the formulation of a conceptual data system was analyzed. Any potential problem areas in meeting these data system requirements were identified in an iterative process.

Downs, S. W.↗

Fault-free behavior of reliable multiprocessor systems: FTMP experiments in AIRLAB

This report describes a set of experiments which were implemented on the Fault tolerant Multi-Processor (FTMP) at NASA/Langley's AIRLAB facility. These experiments are part of an effort to formulate and evaluate validation methodologies for fault-tolerant computers. This report deals with the measurement of single parameters (baselines) of a fault free system. The initial set of baseline experiments lead to the following conclusions: (1) The system clock is constant and independent of workload in the tested cases; (2) the instruction execution times are constant; (3) the R4 frame size is 40mS with some variation; (4) the frame stretching mechanism has some flaws in its implementation that allow the possibility of an infinite stretching of frame duration. Future experiments are planned. Some will broaden the results of these initial experiments. Others will measure the system more dynamically. The implementation of a synthetic workload generation mechanism for FTMP is planned to enhance the experimental environment of the system.

Clune, E.↗

Flutter analysis of low aspect ratio wings

Several very low aspect ratio flat plate wing configurations are analyzed for their aerodynamic instability (flutter) characteristics. All of the wings investigated are delta planforms with clipped tips, made of aluminum alloy plate and cantilevered from the supporting vehicle body. Results of both subsonic and supersonic NASTRAN aeroelastic analyses as well as those from another version of the program implementing the supersonic linearized aerodynamic theory are presented. Results are selectively compared with the experimental data; however, supersonic predictions of the Mach Box method in NASTRAN are found to be erratic and erroneous, requiring the use of a separate program.

Parnell, L. A.↗

Three-dimensional unsteady Euler solutions for propfans and counter-rotating propfans in transonic flow

An Euler code designed for computing the unsteady, three-dimensional, transonic flow about single-rotating and counter-rotating propfans using dynamic blocked-grids is presented. The algorithm is a finite volume, flux-split, upwind, implicit scheme and solves the equations which have been written in a time-dependent curvilinear coordinate system. Relative motion of the blades for counter-rotating configurations is handled by requiring that grid lines be aligned after each discrete rotation of fore and aft rotor grid blocks. The method by which information is passed across block interfaces, as well as how downstream characteristic outflow boundary conditions which enforce simple radial equilibrium are implemented, is discussed. Comparisons of computed flow-field parameters and propfan performance with experimental data indicate good overall agreement between predictions and measurements.

Whitfield, D. L.↗

Thermoelastic Stress Analysis: The Mean Stress Effect in Metallic Alloys

The primary objective of this study involved the utilization of the thermoelastic stress analysis (TSA) method to demonstrate the mean stress dependence of the thermoelastic constant. Titanium and nickel base alloys, commonly employed in aerospace gas turbines, were the materials of interest. The repeatability of the results was studied through a statistical analysis of the data. Although the mean stress dependence was well established, the ability to confidently quantify it was diminished by the experimental variations. If calibration of the thermoelastic response to mean stress can be successfully implemented, it is feasible to use the relationship to determine a structure's residual stress state.

Gyekenyesi, Andrew L.↗

Controls Considerations for Turbine Active Clearance Control

This presentation discusses active control of turbine tip clearance from a control systems perspective. It is a subset of charts that were presented at the 2003 meeting of the International Society of Air Breathing Engines which was held August 31 through September 5 in Cleveland, Ohio. The associated reference paper is cited at the end of the presentation. The presentation describes active tip clearance control research being conducted by NASA to improve turbine engine systems. The target application for this effort is commercial aircraft engines. However, it is believed that the technologies developed as part of this research will benefit a broad spectrum of current and future turbomachinery. The first part of the presentation discusses the concept of tip clearance, problems associated with it, and the benefits of controlling it. It lays out a framework for implementing tip clearance controls that enables the implementation to progress from purely analytical to hardware-in-the-loop to fully experimental. And it briefly discusses how the technologies developed will be married to the previously described ACC Test Rig for hardware-in-the-loop demonstrations. The final portion of the presentation, describes one of the key technologies in some detail by presenting equations and results for a functional dynamic model of the tip clearance phenomena. As shown, the model exhibits many of the clearance dynamics found in commercial gas turbine engines. However, initial attempts to validate the model identified limitations that are being addressed to make the model more realistic.

Melcher, Kevin J.↗

CDEP Consortium on Ocean Data Assimilation for Seasonal-to-Interannual Prediction (ODASI)

The ODASI consortium is focused activity of the NOAA/OGP/Climate Diagnostics and Experimental Prediction Program with the goal of improving ocean data assimilation methods and their implementations in support of seasonal forecasts with coupled general circulation models. The consortium is undertaking coordinated assimilation experiments, with common forcing data sets and common input data streams. With different assimilation systems and different models, we aim to understand what approach works best in improving forecast skill in the equatorial Pacific. The presentation will provide an overview of the consortium goals and plans and recent results focused towards evaluating data impacts.

Rienecker, Michele↗